Flocking Motion, Obstacle Avoidance and Formation Control of Range Limit Perceived Groups Based on Swarm Intelligence Strategy

In nature there are many biological organisms show that the collective behavior in which implicating the potential interior operational principle. Based on the analysis of various biological swarms of dynamic aggregation mechanism, the swarm’s flocking motion, obstacle avoidance and formation behaviour control was studied based on intelligent agents that have limited detection range, an isotropic perceived group dynamic model is proposed in this paper. The theoretical analysis confirm that, based on the strategy of combining artificial potential with velocity consensus, under an interplay between linearly bounded attraction and unbounded repulsion force among the individuals in the group, as a result of security safeguard of the safe distance between individuals, the individuals in the group during the course of coordinative motion can realize the local collision-free stabilization of particular predefined a desired symmetric geometrical configuration formation and mutual aggregating behaviour. Better self-adaptability of surrounding environment is embodied out in the proposed model. The results of simulation show that the algorithm is valid.

[1]  Veysel Gazi,et al.  Formation control with potential functions and Newton's iteration , 2007, 2007 European Control Conference (ECC).

[2]  Guangming Xie,et al.  Flocking Coordination of Multiple Interactive Dynamical Agents with Switching Topology , 2006, 2006 IEEE International Conference on Systems, Man and Cybernetics.

[3]  Zeng Jian-chao Simulation Modeling and Analysis of Dynamics of Range Limit Perceived Group , 2009 .

[4]  Liang Chen,et al.  Collective Behavior of an Anisotropic Swarm Model Based on Unbounded Repulsion in Social Potential Fields , 2006, ICIC.

[5]  J G Walker The Geometry of Satellite Clusters. , 1981 .

[6]  YangQuan Chen,et al.  Formation control: a review and a new consideration , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[7]  Baris Fidan,et al.  Coordination and Control of Multi-agent Dynamic Systems: Models and Approaches , 2006, Swarm Robotics.

[8]  C.M. Saaj,et al.  Spacecraft Swarm Navigation and Control Using Artificial Potential Field and Sliding Mode Control , 2006, 2006 IEEE International Conference on Industrial Technology.

[9]  Yong-Ji Wang,et al.  Stable flocking motion of mobile agents following a leader in fixed and switching networks , 2006, Int. J. Autom. Comput..

[10]  Baris Fidan,et al.  Aggregation, Foraging, and Formation Control of Swarms with Non-Holonomic Agents Using Potential Functions and Sliding Mode Techniques ∗† , 2007 .

[11]  Huajing Fang,et al.  Modeling and stability analysis of social foraging swarms in multi-obstacle environment , 2006 .